学术文献库

Negative environmental impacts on societies and ecosystems are frequently driven by human activity and amplified by increasing climatic variability. Properly managing these impacts relies on a government's ability to ensure environmental regulatory compliance in the face of increasing uncertainty. Water flow rates are the most widely used evaluation metric for river regulatory compliance. Specifically, compliance thresholds are set by calculating the minimum flow rates required by aquatic species such as fish. These are then designated as the minimum "environmental flows" (eflows) for each river. In this paper, we explore how IoT-generated open government data can be used to enhance the development of an automated IoT-based eflows compliance system. To reduce development and operational costs, the proposed solution relies on routinely collected river monitoring data. Our approach allows for any authority with similar data to rapidly develop, test and verify a scalable solution for eflow regulatory compliance monitoring and evaluation. Furthermore, we demonstrate a real-world application of our system using open government data from Estonia's national river monitoring network. The main novelty of this work is that the proposed IoT-based system provides a simple evaluation tool that re-purposes IoT-generated open government data to evaluate compliance and improve monitoring at a national scale. This work showcases a new paradigm of IoT-based solutions using open government data and provides a real-world example of how the solution can automatically evaluate environmental compliance in increasingly uncertain environments.